Showing 1-4 of 4 results

Juan Manuel Ortiz de Zarate

Ensemble Methods: The Kaggle Machine Learning Champion

By Juan Manuel Ortiz de Zarate
Two heads are better than one. This proverb describes the concept behind ensemble methods in machine learning. Let's examine why ensembles dominate ML competitions and what makes them so powerful.
9 minute readContinue Reading
Neven Pičuljan

Schooling Flappy Bird: A Reinforcement Learning Tutorial

By Neven Pičuljan
Leveraging DeepMind's breakthrough AI approaches takes some work, but the results are astounding. In this article, Toptal Freelance Deep Learning Engineer Neven Pičuljan guides us through the building blocks of reinforcement learning, training a neural network to play Flappy Bird using the PyTorch framework.
17 minute readContinue Reading
Peter Hussami

How to Approach Machine Learning Problems

By Peter Hussami
How do you approach machine learning problems? Are neural networks the answer to nearly every challenge you may encounter? In this article, Toptal Freelance Python Developer Peter Hussami explains the basic approach to machine learning problems and points out where neural may fall short.
8 minute readContinue Reading
Cody Nash

Create Data From Random Noise With Generative Adversarial Networks

By Cody Nash
Generative adversarial networks, among the most important machine learning breakthroughs of recent times, allow you to generate useful data from random noise. Instead of training one neural network with millions of data points, you let two neural networks contest with each other to figure things out. In this article, Toptal Freelance Software Engineer Cody Nash gives us an overview of how GANs work and how this class of machine learning algorithms can be used to generate data in data-limited situations.
13 minute readContinue Reading

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